Robotics and Automation in Agriculture: Present and Future Applications

Agriculture is the backbone of society as it mainly functions to provide food, feed and fiber on which all human depends to live. Precision agriculture is implemented with a goal to apply sufficient treatments at the right place in the right time with the purpose to provide low-input, high efficiency and sustainable agricultural production. In precision agriculture, automation and robotics have become one of the main frameworks which focusing on minimizing environmental impact and simultaneously maximizing agricultural produce. The application of automation and robotics in precision agriculture is essentially implemented for precise farm management by using modern technologies. In the past decades, a significant amount of research has focused on the applications of mobile robot for agricultural operations such as planting, inspection, spraying and harvesting. This paper reviews the recent applications of automation and robotics in agriculture in the past five years. In this paper, the recent implementations are divided into four categories which indicates different operations executed for planting management starting from a seed until the product is ready to be harvested. Towards the end of this paper, several challenges and suggestions are described to indicate the opportunities and improvements that can be made in designing an efficient autonomous and robotics system for agricultural applications. Based on the conducted review, different operations have different challenges thus require diverse solutions to solve the specific operational problem. Therefore, the development process of an efficient autonomous agricultural robotic system must consider all possibilities and challenges in different types of agricultural operation to minimize system errors during future implementation. In addition, the development cost needs to be fully considered to ensure that the farmers will be able to invest their capital as a consumer. Therefore, it will become highly possible for the autonomous agricultural robotic system to be widely implemented throughout the world in the future.

[1]  K. Abdan,et al.  Automated spray up process for Pineapple Leaf Fibre hybrid biocomposites , 2019, Composites Part B: Engineering.

[2]  Juan Agüera,et al.  Autonomous systems for precise spraying – Evaluation of a robotised patch sprayer , 2016 .

[3]  Li Yang,et al.  Development of a variable-rate seeding control system for corn planters Part II: Field performance , 2019, Comput. Electron. Agric..

[4]  Chao Chen,et al.  Fast implementation of real-time fruit detection in apple orchards using deep learning , 2020, Comput. Electron. Agric..

[5]  Amir Shapiro,et al.  A novel data fusion algorithm for low-cost localisation and navigation of autonomous vineyard sprayer robots , 2016 .

[6]  Li Yang,et al.  Development of a variable-rate seeding control system for corn planters Part I: Design and laboratory experiment , 2019, Comput. Electron. Agric..

[7]  Bruce MacDonald,et al.  Robotic kiwifruit harvesting using machine vision, convolutional neural networks, and robotic arms , 2019, Biosystems Engineering.

[8]  Yongjie Cui,et al.  Design and simulation of an integrated end-effector for picking kiwifruit by robot , 2020 .

[9]  Fabio Bruno,et al.  Design, prototyping and testing of a modular small-sized underwater robotic arm controlled through a Master-Slave approach , 2018, Ocean Engineering.

[10]  M. Vega-Heredia,et al.  Design and modelling of a modular window cleaning robot , 2019, Automation in Construction.

[11]  Dean Zhao,et al.  Apple tree branch segmentation from images with small gray-level difference for agricultural harvesting robot , 2016 .

[13]  André Carlos Ponce de Leon Ferreira de Carvalho,et al.  An adaptive approach for UAV-based pesticide spraying in dynamic environments , 2017, Comput. Electron. Agric..

[14]  Anil Cay,et al.  Development of an electro-mechanic control system for seed-metering unit of single seed corn planters Part II: Field performance , 2018, Comput. Electron. Agric..

[15]  Mehmet Emin Tenekeci,et al.  Detection of pepper fusarium disease using machine learning algorithms based on spectral reflectance , 2020, Sustain. Comput. Informatics Syst..

[16]  Lei Zhang,et al.  Detection of peanut leaf spots disease using canopy hyperspectral reflectance , 2019, Comput. Electron. Agric..

[17]  Jochen Hemming,et al.  Performance Evaluation of a Harvesting Robot for Sweet Pepper , 2017, J. Field Robotics.

[18]  Robert Mahony,et al.  A Perception Pipeline for Robotic Harvesting of Green Asparagus , 2019, IFAC-PapersOnLine.

[19]  Alexander Wendel,et al.  Spectral filter design based on in-field hyperspectral imaging and machine learning for mango ripeness estimation , 2019, Comput. Electron. Agric..

[20]  Harish Kumar Sardana,et al.  Image acquisition techniques for assessment of legume quality , 2015 .

[21]  Lars Grimstad,et al.  Development and field evaluation of a strawberry harvesting robot with a cable-driven gripper , 2019, Comput. Electron. Agric..

[22]  M. Nogués,et al.  Development of an easily adaptable three-point hitch dynamometer for agricultural tractors. Analysis of the disruptive effects on the measurements , 2019, Soil and Tillage Research.

[23]  Yang Yu,et al.  Fruit detection for strawberry harvesting robot in non-structural environment based on Mask-RCNN , 2019, Comput. Electron. Agric..

[24]  Tao Wang,et al.  Dual-arm cooperation and implementing for robotic harvesting tomato using binocular vision , 2019, Robotics Auton. Syst..

[25]  Jun Chen,et al.  Experimental and simulation analysis of optimum picking patterns for robotic apple harvesting , 2020 .

[26]  Yang Tao,et al.  Automatic inspection machine for maize kernels based on deep convolutional neural networks , 2019, Biosystems Engineering.

[27]  A. Khalina,et al.  The effect of different linear robot travel speed on mass flowrate of pineapple leaf fibre (PALF) automated spray up composite , 2019, Composites Part B: Engineering.

[28]  Josse De Baerdemaeker,et al.  Development of a Robot for Harvesting Strawberries , 2018 .

[29]  Jan Tommy Gravdahl,et al.  Robotic in-row weed control in vegetables , 2018, Comput. Electron. Agric..

[30]  Yong He,et al.  Computer vision-based localisation of picking points for automatic litchi harvesting applications towards natural scenarios , 2019, Biosystems Engineering.

[31]  Noboru Noguchi,et al.  Development and application of a wheel-type robot tractor , 2016 .

[32]  Xin Wang,et al.  Structure Design and Image Recognition Research of A Picking Device on the Apple Picking Robot , 2018 .

[33]  Subrat Kar,et al.  Automation of Agriculture Support Systems using Wisekar: Case study of a crop-disease advisory service , 2016, Comput. Electron. Agric..

[34]  Saeid Minaei,et al.  Ultrasonic sensing of pistachio canopy for low-volume precision spraying , 2015, Comput. Electron. Agric..

[35]  Mohamed M. Khairy,et al.  An IoT-based cognitive monitoring system for early plant disease forecast , 2019, Comput. Electron. Agric..

[36]  Xiong Chen,et al.  A vision methodology for harvesting robot to detect cutting points on peduncles of double overlapping grape clusters in a vineyard , 2018, Comput. Ind..

[37]  Marsyita Hanafi,et al.  Application of laser-induced backscattering imaging for predicting and classifying ripening stages of "Berangan" bananas , 2019, Comput. Electron. Agric..

[38]  Shimon Y. Nof,et al.  Agricultural cyber physical system collaboration for greenhouse stress management , 2018, Comput. Electron. Agric..

[39]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[40]  A. K. Misra,et al.  Detection of plant leaf diseases using image segmentation and soft computing techniques , 2017 .

[41]  Yuanshen Zhao,et al.  A review of key techniques of vision-based control for harvesting robot , 2016, Comput. Electron. Agric..

[42]  Shishir K. Shandilya,et al.  IoT in Agriculture Investigation on Plant Diseases and Nutrient Level Using Image Analysis Techniques , 2019, Internet of Things in Biomedical Engineering.

[43]  Aldo Calcante,et al.  Selective spraying of grapevines for disease control using a modular agricultural robot , 2016 .

[44]  Marco Grella,et al.  Effect of sprayer settings on spray drift during pesticide application in poplar plantations (Populus spp.). , 2017, The Science of the total environment.

[45]  Qi Zhang,et al.  An ultrasensitive gray-imaging-based quantitative immunochromatographic detection method for fumonisin B1 in agricultural products , 2017 .

[46]  D. B. Myers,et al.  Relating planter downforce and soil strength , 2018, Soil and Tillage Research.

[47]  Jochen Hemming,et al.  Angle estimation between plant parts for grasp optimisation in harvest robots , 2019, Biosystems Engineering.

[48]  Baohua Zhang,et al.  Comparative study of mechanical damage caused by a two-finger tomato gripper with different robotic grasping patterns for harvesting robots , 2018, Biosystems Engineering.

[49]  Elizabeth M. Musiu,et al.  Spray deposition and distribution on the targets and losses to the ground as affected by application volume rate, airflow rate and target position , 2019, Crop Protection.

[50]  Abdelhak Mourad Guéroui,et al.  Concepts and evolution of research in the field of wireless sensor networs , 2015, ArXiv.

[51]  Predicting header wheat loss in a combine harvester, a new approach , 2020 .

[52]  Zahid Iqbal,et al.  Detection and classification of citrus diseases in agriculture based on optimized weighted segmentation and feature selection , 2018, Comput. Electron. Agric..

[53]  Noboru Noguchi,et al.  Heavy-weight Crop Harvesting Robot - Controlling Algorithm , 2018 .

[54]  James Patrick Underwood,et al.  Image Based Mango Fruit Detection, Localisation and Yield Estimation Using Multiple View Geometry , 2016, Sensors.

[55]  Aleksandr Andrejcuk,et al.  Autonomous control for multi-agent non-uniform spraying , 2019, Appl. Soft Comput..

[56]  Stuart Bradley,et al.  Evaluation of a Spray Scheduling System , 2016 .

[57]  Michihisa Iida,et al.  Multi-objective path planner for an agricultural mobile robot in a virtual greenhouse environment , 2019, Comput. Electron. Agric..

[58]  Jochen Hemming,et al.  Analysis of a motion planning problem for sweet-pepper harvesting in a dense obstacle environment , 2016 .

[59]  Amir Shapiro,et al.  Advances in robotic agriculture for crops , 2016 .

[60]  Hossein Navid,et al.  Development of an infrared seed-sensing system to estimate flow rates based on physical properties of seeds , 2019, Comput. Electron. Agric..

[61]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[62]  Luisa Martelloni,et al.  Development of a prototype of telemetry system for monitoring the spraying operation in vineyards , 2017, Comput. Electron. Agric..

[63]  E. Taira,et al.  Effect of metering device arrangement to discharge consistency of sugarcane billet planter , 2018, Engineering in Agriculture, Environment and Food.

[64]  Jim Euchner.  Design , 2014, Catalysis from A to Z.

[65]  Jafar Massah,et al.  A farmer-assistant robot for nitrogen fertilizing management of greenhouse crops , 2017, Comput. Electron. Agric..

[66]  Kemal Adem,et al.  Automatic detection and classification of leaf spot disease in sugar beet using deep learning algorithms , 2019, Physica A: Statistical Mechanics and its Applications.

[67]  Jordi Llorens,et al.  Fruit detection in an apple orchard using a mobile terrestrial laser scanner , 2019, Biosystems Engineering.

[68]  Virendra. V. Shete,et al.  Precision agriculture robot for seeding function , 2016, 2016 International Conference on Inventive Computation Technologies (ICICT).

[69]  P.C.H. Miller,et al.  Control requirements for spatially selective herbicide sprayers , 1996 .

[70]  R. Karthik,et al.  Attention embedded residual CNN for disease detection in tomato leaves , 2020, Appl. Soft Comput..

[71]  Hesham Abd-El Monsef,et al.  Using multispectral imagery to extract a pure spectral canopy signature for predicting peanut maturity , 2019, Comput. Electron. Agric..

[73]  Xiaochan Wang,et al.  Numerical simulation and field tests of minimum-tillage planter with straw smashing and strip laying based on EDEM software , 2019, Comput. Electron. Agric..

[74]  Christoph Schuetz,et al.  CROPS Agricultural Robot: Application to Selective Spraying of Grapevine's Diseases , 2014 .

[75]  Study on Precision Application Rate Technology for maize no-tillage planter in North China Plain , 2018 .

[76]  Eldert J. van Henten,et al.  Design of an eye-in-hand sensing and servo control framework for harvesting robotics in dense vegetation , 2016 .

[77]  Amir Degani,et al.  A conceptual framework and optimization for a task-based modular harvesting manipulator , 2019, Comput. Electron. Agric..

[78]  Matt J. Aitkenhead,et al.  Detection and differentiation between potato (Solanum tuberosum) diseases using calibration models trained with non-imaging spectrometry data , 2019, Comput. Electron. Agric..

[79]  Wang Yijie,et al.  A method to obtain the near-large fruit from apple image in orchard for single-arm apple harvesting robot , 2019, Scientia Horticulturae.

[80]  Brane Širok,et al.  Close-range air-assisted precision spot-spraying for robotic applications: Aerodynamics and spray coverage analysis , 2016 .

[81]  Heng Wang,et al.  Simulation As A Tool In Designing And Evaluating A Robotic Apple Harvesting System , 2018 .

[82]  Angela Ribeiro,et al.  Route planning for agricultural tasks: A general approach for fleets of autonomous vehicles in site-specific herbicide applications , 2016, Comput. Electron. Agric..

[83]  Anil Cay,et al.  Development of an electro-mechanic control system for seed-metering unit of single seed corn planters Part I: Design and laboratory simulation , 2018, Comput. Electron. Agric..

[84]  Syed Ahmad Chan Bukhari,et al.  A citrus fruits and leaves dataset for detection and classification of citrus diseases through machine learning , 2019, Data in brief.

[85]  Farangis Khosro Anjom,et al.  Development of a linear mixed model to predict the picking time in strawberry harvesting processes , 2018 .

[86]  Danna Zhou,et al.  d. , 1934, Microbial pathogenesis.

[87]  Adam Březina,et al.  Design of a Prototype for a Modular Mobile Robotic Platform , 2019 .

[88]  Zhe Zhang,et al.  End-effector with a bite mode for harvesting citrus fruit in random stalk orientation environment , 2019, Comput. Electron. Agric..

[89]  Yong He,et al.  Detection of orchard citrus fruits using a monocular machine vision-based method for automatic fruit picking applications , 2018, Comput. Electron. Agric..

[90]  Zahra Abdolahzare,et al.  Real time laboratory and field monitoring of the effect of the operational parameters on seed falling speed and trajectory of pneumatic planter , 2018, Comput. Electron. Agric..